Lecture 25

1. Lecture 25 Enterprise Systems Development ( CSC447) COMSATS Islamabad Muhammad Usman, Assistant Professor

2. Service-oriented design: design sub-steps Service oriented analysis step 1 Compose SOA Service oriented design step 2 Design entity-centric business services step 3 Design infrastructure services ... step 4 Design task-centric business services step 5 Design SO business process

3. Receive PO document Invoice PO 1 * * <<include>> ... Customer Hours billed * Validate PO document * 1 PO processing service * ... 1 (If PO document is invalid,) send rejection notification (and end process) 1 1 Employee Order * Email Weekly hours ... <<include>> Transform PO document into native electronic PO format 1 * Customer 1 ... 1 Entity-centric business services • Goal: entity-centric business service layer + parent orchestration layer

4. Infrastructure services PO processing service Orchestration/coordination layer Verify PO service PO service Business service layer Infrastructure service layer Transform service Notification service

5. Receive PO document <<include>> Validate PO document PO processing service ... (If PO document is invalid,) send rejection notification (and end process) <<include>> Transform PO document into native electronic PO format Task-centric business services • UML sequence diagram • express and refine order of invocations implicit in the UML use case diagram Verify PO service PO service Notification service get_PO [PO data] verify send_reject

6. Database Design

7. Database Management System (DBMS) • DBMS contains information about a particular enterprise • Collection of interrelated data • Set of programs to access the data • An environment that is both convenient and efficient to use • Database Applications: • Banking: all transactions • Airlines: reservations, schedules • Universities: registration, grades • Sales: customers, products, purchases • Online retailers: order tracking, customized recommendations • Manufacturing: production, inventory, orders, supply chain • Human resources: employee records, salaries, tax deductions • Databases touch all aspects of our lives

8. Purpose of Database Systems • In the early days, database applications were built directly on top of file systems • Drawbacks of using file systems to store data: • Data redundancy and inconsistency • Multiple file formats, duplication of information in different files • Difficulty in accessing data • Need to write a new program to carry out each new task • Data isolation — multiple files and formats • Integrity problems • Integrity constraints (e.g. account balance > 0) become “buried” in program code rather than being stated explicitly • Hard to add new constraints or change existing ones

9. Purpose of Database Systems (Cont.) • Drawbacks of using file systems (cont.) • Atomicity of updates • Failures may leave database in an inconsistent state with partial updates carried out • Example: Transfer of funds from one account to another should either complete or not happen at all • Concurrent access by multiple users • Concurrent accessed needed for performance • Uncontrolled concurrent accesses can lead to inconsistencies • Example: Two people reading a balance and updating it at the same time • Security problems • Hard to provide user access to some, but not all, data • Database systems offer solutions to all the above problems

10. Levels of Abstraction • Physical level: describes how a record (e.g., customer) is stored. • Logical level: describes data stored in database, and the relationships among the data. typecustomer = record customer_id : string; customer_name : string;customer_street : string;customer_city : string; end; • View level: application programs hide details of data types. Views can also hide information (such as an employee’s salary) for security purposes.

11. View of Data An architecture for a database system

12. Instances and Schemas • Similar to types and variables in programming languages • Schema – the logical structure of the database • Example: The database consists of information about a set of customers and accounts and the relationship between them) • Analogous to type information of a variable in a program • Physical schema: database design at the physical level • Logical schema: database design at the logical level • Instance – the actual content of the database at a particular point in time • Analogous to the value of a variable • Physical Data Independence – the ability to modify the physical schema without changing the logical schema • Applications depend on the logical schema • In general, the interfaces between the various levels and components should be well defined so that changes in some parts do not seriously influence others.

13. Data Models • A collection of tools for describing • Data • Data relationships • Data semantics • Data constraints • Relational model • Entity-Relationship data model (mainly for database design) • Object-based data models (Object-oriented and Object-relational) • Semistructured data model (XML) • Other older models: • Network model • Hierarchical model

14. Data Manipulation Language (DML) • Language for accessing and manipulating the data organized by the appropriate data model • DML also known as query language • Two classes of languages • Procedural – user specifies what data is required and how to get those data • Declarative (nonprocedural) – user specifies what data is required without specifying how to get those data • SQL is the most widely used query language

15. Data Definition Language (DDL) • Specification notation for defining the database schema Example: create tableaccount (account_numberchar(10), branch_name char(10), balanceinteger) • DDL compiler generates a set of tables stored in a data dictionary • Data dictionary contains metadata (i.e., data about data) • Database schema • Data storage and definition language • Specifies the storage structure and access methods used • Integrity constraints • Domain constraints • Referential integrity (e.g. branch_name must correspond to a valid branch in the branch table) • Authorization

16. Relational Model Attributes • Example of tabular data in the relational model

17. A Sample Relational Database

18. SQL • SQL: widely used non-procedural language • Example: Find the name of the customer with customer-id 192-83-7465select customer.customer_namefrom customerwherecustomer.customer_id = ‘192-83-7465’ • Example: Find the balances of all accounts held by the customer with customer-id 192-83-7465selectaccount.balancefromdepositor, accountwheredepositor.customer_id = ‘192-83-7465’ anddepositor.account_number = account.account_number • Application programs generally access databases through one of • Language extensions to allow embedded SQL • Application program interface (e.g., ODBC/JDBC) which allow SQL queries to be sent to a database

19. Database Design The process of designing the general structure of the database: • Logical Design – Deciding on the database schema. Database design requires that we find a “good” collection of relation schemas. • Business decision – What attributes should we record in the database? • Computer Science decision – What relation schemas should we have and how should the attributes be distributed among the various relation schemas? • Physical Design – Deciding on the physical layout of the database

20. The Entity-Relationship Model • Models an enterprise as a collection of entities and relationships • Entity: a “thing” or “object” in the enterprise that is distinguishable from other objects • Described by a set of attributes • Relationship: an association among several entities • Represented diagrammatically by an entity-relationship diagram:

21. Other Data Models • Object-oriented data model • Object-relational data model

22. Database Application Architectures (web browser) Modern Old

23. Database Management System Internals • Storage management • Query processing • Transaction processing

24. Storage Management • Storage manager is a program module that provides the interface between the low-level data stored in the database and the application programs and queries submitted to the system. • The storage manager is responsible to the following tasks: • Interaction with the file manager • Efficient storing, retrieving and updating of data • Issues: • Storage access • File organization • Indexing and hashing

25. Query Processing 1. Parsing and translation 2. Optimization 3. Evaluation

26. Query Processing (Cont.) • Alternative ways of evaluating a given query • Equivalent expressions • Different algorithms for each operation • Cost difference between a good and a bad way of evaluating a query can be enormous • Need to estimate the cost of operations • Depends critically on statistical information about relations which the database must maintain • Need to estimate statistics for intermediate results to compute cost of complex expressions

27. Transaction Management • A transaction is a collection of operations that performs a single logical function in a database application • Transaction-management component ensures that the database remains in a consistent (correct) state despite system failures (e.g., power failures and operating system crashes) and transaction failures. • Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database.

28. Overall System Structure

29. History of Database Systems • 1950s and early 1960s: • Data processing using magnetic tapes for storage • Tapes provide only sequential access • Punched cards for input • Late 1960s and 1970s: • Hard disks allow direct access to data • Network and hierarchical data models in widespread use • Ted Codd defines the relational data model • Would win the ACM Turing Award for this work • IBM Research begins System R prototype • UC Berkeley begins Ingres prototype • High-performance (for the era) transaction processing

30. History (cont.) • 1980s: • Research relational prototypes evolve into commercial systems • SQL becomes industry standard • Parallel and distributed database systems • Object-oriented database systems • 1990s: • Large decision support and data-mining applications • Large multi-terabyte data warehouses • Emergence of Web commerce • 2000s: • XML and XQuery standards • Automated database administration • Increasing use of highly parallel database systems • Web-scale distributed data storage systems

31. RELATIONAL mODEL

32. Example of a Relation

33. Attribute Types • Each attribute of a relation has a name • The set of allowed values for each attribute is called the domain of the attribute • Attribute values are (normally) required to be atomic; that is, indivisible • E.g. the value of an attribute can be an account number, but cannot be a set of account numbers • Domain is said to be atomic if all its members are atomic • The special value null is a member of every domain • The null value causes complications in the definition of many operations

34. Relation Schema • Formally, given domains D1, D2, …. Dn a relation r is a subset of D1 x D2 x … x DnThus, a relation is a set of n-tuples (a1, a2, …, an) where each ai Di • Schema of a relation consists of • attribute definitions • name • type/domain • integrity constraints

35. Relation Instance • The current values (relation instance) of a relation are specified by a table • An element t of r is a tuple, represented by a row in a table • Order of tuples is irrelevant (tuples may be stored in an arbitrary order) attributes (or columns) customer_name customer_street customer_city Jones Smith Curry Lindsay Main North North Park Harrison Rye Rye Pittsfield tuples (or rows) customer

36. Database • A database consists of multiple relations • Information about an enterprise is broken up into parts, with each relation storing one part of the information • E.g. account : information about accountsdepositor : which customer owns which account customer : information about customers

37. The customer Relation

38. The depositor Relation

39. Why Split Information Across Relations? • Storing all information as a single relation such as bank(account_number, balance, customer_name, ..)results in • repetition of information • e.g.,if two customers own an account (What gets repeated?) • the need for null values • e.g., to represent a customer without an account • Normalization theory deals with how to design relational schemas

40. Keys • Let K  R • K is a superkey of R if values for K are sufficient to identify a unique tuple of each possible relation r(R) • by “possible r ” we mean a relation r that could exist in the enterprise we are modeling. • Example: {customer_name, customer_street} and {customer_name} are both superkeys of Customer, if no two customers can possibly have the same name • In real life, an attribute such as customer_id would be used instead of customer_name to uniquely identify customers, but we omit it to keep our examples small, and instead assume customer names are unique.

41. Keys (Cont.) • K is a candidate key if K is minimalExample: {customer_name} is a candidate key for Customer, since it is a superkey and no subset of it is a superkey. • Primary key: a candidate key chosen as the principal means of identifying tuples within a relation • Should choose an attribute whose value never, or very rarely, changes. • E.g. email address is unique, but may change

42. Foreign Keys • A relation schema may have an attribute that corresponds to the primary key of another relation. The attribute is called a foreign key. • E.g. customer_name and account_number attributes of depositor are foreign keys to customer and account respectively. • Only values occurring in the primary key attribute of the referenced relation may occur in the foreign key attribute of the referencing relation.

43. Schema Diagram

44. Query Languages • Language in which user requests information from the database. • Categories of languages • Procedural • Non-procedural, or declarative • “Pure” languages: • Relational algebra • Tuple relational calculus • Domain relational calculus • Pure languages form underlying basis of query languages that people use.

45. Relational Algebra • Procedural language • Six basic operators • select:  • project:  • union:  • set difference: – • Cartesian product: x • rename:  • The operators take one or two relations as inputs and produce a new relation as a result.

46. Select Operation – Example • Relation r A B C D         1 5 12 23 7 7 3 10 • A=B ^ D > 5(r) A B C D     1 23 7 10

47. Project Operation – Example A B C • Relation r:     10 20 30 40 1 1 1 2 A C A C A,C (r)     1 1 1 2    1 1 2 =

48. Union Operation – Example • Relations r, s: A B A B    1 2 1   2 3 s r A B     1 2 1 3 • r  s:

49. Set Difference Operation – Example • Relations r, s: A B A B    1 2 1   2 3 s r • r – s: A B   1 1

50. Cartesian-Product Operation – Example • Relations r, s: A B C D E   1 2     10 10 20 10 a a b b r s • r xs: A B C D E         1 1 1 1 2 2 2 2         10 10 20 10 10 10 20 10 a a b b a a b b